Integrated image-based deep learning and language models for primary diabetes care.

Primary diabetes care and diabetic retinopathy (DR) screening persist as major public health challenges due to a shortage of trained primary care physicians (PCPs), particularly in low-resource settings. Here, to bridge the gaps, we developed an integrated image-language system (DeepDR-LLM), combining a large language model (LLM module) and image-based deep learning (DeepDR-Transformer), to provide individualized diabetes management recommendations to PCPs. In a retrospective evaluation, the LLM module demonstrated comparable performance to PCPs and endocrinology residents when tested in English and outperformed PCPs and had comparable performance to endocrinology residents in Chinese. For identifying referable DR, the average PCP's accuracy was 81.0% unassisted and 92.3% assisted by DeepDR-Transformer. Furthermore, we performed a single-center real-world prospective study, deploying DeepDR-LLM. We compared diabetes management adherence of patients under the unassisted PCP arm (n = 397) with those under the PCP+DeepDR-LLM arm (n = 372). Patients with newly diagnosed diabetes in the PCP+DeepDR-LLM arm showed better self-management behaviors throughout follow-up (P < 0.05). For patients with referral DR, those in the PCP+DeepDR-LLM arm were more likely to adhere to DR referrals (P < 0.01). Additionally, DeepDR-LLM deployment improved the quality and empathy level of management recommendations. Given its multifaceted performance, DeepDR-LLM holds promise as a digital solution for enhancing primary diabetes care and DR screening.

Higher risk of incident diabetes among patients with primary hyperparathyroidism.

OBJECTIVES: There is relatively scarce data regarding the association between primary hyperparathyroidism (PHPT) and incident diabetes in large population-based longitudinal studies. We aimed to evaluate the risk of incident diabetes in individuals with and without PHPT and investigate the association between serum calcium concentrations and the risk of incident diabetes in patients with PHPT. METHODS: We included 2749 PHPT patients and 13,745 age, sex and index year matched non-PHPT individuals during 2000-2019. We used Cox regression models to compare the risk of incident diabetes in individuals with and without PHPT, and the risk of incident diabetes in PHPT patients with serum calcium concentration above and below the median value. The association between serum calcium concentrations and the risk of incident diabetes was examined by restricted cubic spline analyses in patients with PHPT. RESULTS: During a median follow-up time of 5.17 years (IQR 2.17, 9.58), 433 patients (15.75%) with PHPT and 2110 individuals (15.35%) without PHPT developed diabetes, respectively. Patients with PHPT had a higher incidence rate of diabetes compared to non-PHPT individuals (27.60 [95% CI 25.00, 30.30] vs. 23.90 [95% CI 22.80, 24.90] per 1000 person-years, log-rank test p = .007]. Crude Cox regression model showed PHPT was associated with a 15% higher risk of incident diabetes (HR 1.15, 95%CI 1.04, 1.28). In patients with PHPT, a 44% higher risk of incident diabetes was found in patients with serum calcium concentrations above the median value (2.63 mmol/L), compared to those below the median value (HR 1.44, 95%CI 1.08, 1.90). Restricted cubic spline analyses confirmed a positive linear association between serum calcium concentrations and the risk of incident diabetes in those with PHPT (p-value for nonlinear = .751) CONCLUSIONS: Patients with PHPT had a higher risk of incident diabetes compared to non-PHPT individuals. A positive linear association was found between serum calcium concentrations and the risk of incident diabetes in patients with PHPT.

Impaired GK-GKRP interaction rather than direct GK activation worsens lipid profiles and contributes to long-term complications: a Mendelian randomization study.

BACKGROUND: Glucokinase (GK) plays a key role in glucose metabolism. In the liver, GK is regulated by GK regulatory protein (GKRP) with nuclear sequestration at low plasma glucose level. Some GK activators (GKAs) disrupt GK-GKRP interaction which increases hepatic cytoplasmic GK level. Excess hepatic GK activity may exceed the capacity of glycogen synthesis with excess triglyceride formation. It remains uncertain whether hypertriglyceridemia associated with some GKAs in previous clinical trials was due to direct GK activation or impaired GK-GKRP interaction. METHODS: Using publicly available genome-wide association study summary statistics, we selected independent genetic variants of GCKR and GCK associated with fasting plasma glucose (FPG) as instrumental variables, to mimic the effects of impaired GK-GKRP interaction and direct GK activation, respectively. We applied two-sample Mendelian Randomization (MR) framework to assess their causal associations with lipid-related traits, risks of metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular diseases. We verified these findings in one-sample MR analysis using individual-level statistics from the Hong Kong Diabetes Register (HKDR). RESULTS: Genetically-proxied impaired GK-GKRP interaction increased plasma triglycerides, low-density lipoprotein cholesterol and apolipoprotein B levels with increased odds ratio (OR) of 14.6 (95% CI 4.57-46.4) per 1 mmol/L lower FPG for MASLD and OR of 2.92 (95% CI 1.78-4.81) for coronary artery disease (CAD). Genetically-proxied GK activation was associated with decreased risk of CAD (OR 0.69, 95% CI 0.54-0.88) and not with dyslipidemia. One-sample MR validation in HKDR showed consistent results. CONCLUSIONS: Impaired GK-GKRP interaction, rather than direct GK activation, may worsen lipid profiles and increase risks of MASLD and CAD. Development of future GKAs should avoid interfering with GK-GKRP interaction.

Association of dipeptidyl peptidase-4 inhibitor initiation at glycated haemoglobin <7.5% with reduced major clinical events mediated by low glycated haemoglobin variability.

AIM: Therapeutic inertia, hypoglycaemia and poor treatment persistence can lead to glycaemic fluctuation and poor outcomes in type 2 diabetes (T2D). We compared glycated haemoglobin (HbA1c) variability, insulin initiation, severe hypoglycaemia and clinical events in patients with T2D initiated dipeptidyl peptidase-4 inhibitors (DPP4is) at low versus high HbA1c thresholds. METHODS: Using territory-wide electronic medical records in Hong Kong, we curated a propensity score-matched cohort of patients initiated DPP4i at HbA1c <7.5% versus ≥7.5% in 2007-2019. We expressed the HbA1c variability score (HVS) as a proportion of HbA1c varied by ≥0.5% compared with preceding values. We used the Cox model to compare the risks of insulin initiation and clinical outcomes, adjusted for time-varying variables between the two groups. Mediation analysis estimated the effects of HbA1c variability on outcomes. RESULTS: Among 6874 insulin-naïve patients who initiated DPP4i, 88.7% were treated with metformin and 79.6% with sulphonylureas at baseline (54.9% men; mean age 65.2 ± 11.4 years). After a median follow-up of 4.6 years, compared with the high-threshold plus high-HVS group (≥50%), the low-threshold plus low-HVS (<50%) group had reduced hazard ratios (95% confidence interval) of insulin initiation (0.35, 0.31-0.40), severe hypoglycaemia (0.38, 0.34-0.44), major adverse cardiovascular endpoints (0.76, 0.66-0.88), heart failure (0.42, 0.36-0.49), end-stage kidney disease (0.65, 0.36-0.49) and mortality (0.45, 0.35-0.57). Reduced HbA1c variability explained 31.1%-81.2% of the effect size of DPP4i initiation at HbA1c <7.5% versus ≥7.5% on outcomes. CONCLUSIONS: In Chinese patients with T2D, avoiding therapeutic inertia with intensified glycaemic control at HbA1c <7.5% using drugs with low risk of hypoglycaemia and good tolerability, such as DPP4i, delayed insulin treatment, reduced HbA1c variability and improved clinical events.

Monogenic diabetes in a Chinese population with young-onset diabetes: A 17-year prospective follow-up study in Hong Kong.

AIMS: Asians have a high prevalence of young-onset diabetes, but the pattern of monogenic diabetes is unknown. We aimed to determine the prevalence of monogenic diabetes in Chinese patients with young-onset diabetes and compare the clinical characteristics and outcome between patients with and without monogenic diabetes. MATERIALS AND METHODS: We sequenced a targeted panel of 33 genes related to monogenic diabetes in 1021 Chinese patients with non-type 1 diabetes diagnosed at age ≤40 years. Incident complications including cardiovascular disease (CVD), end-stage kidney disease (ESKD) and all-cause death were captured since enrolment (1995-2012) until 2019. RESULTS: In this cohort (mean ± SD age at diagnosis: 33.0 ± 6.0 years, median[IQR] diabetes duration 7.0[1.0-15.0] years at baseline, 44.9% men), 22(2.2%, 95% confidence interval[CI] 1.4%-3.2%) had monogenic diabetes. Pathogenic (P) or likely pathogenic (LP) variants were detected in GCK (n = 6), HNF1A (n = 9), HNF4A (n = 1), PLIN1 (n = 1) and PPARG (n = 2), together with copy number variations in HNF1B (n = 3). Over a median follow-up of 17.1 years, 5(22.7%) patients with monogenic diabetes (incidence rate 12.3[95% CI 5.1-29.4] per 1000 person-years) versus 254(25.4%) without monogenic diabetes (incidence rate 16.7[95% CI 14.8-18.9] per 1000 person-years) developed the composite outcome of CVD, ESKD and/or death (p = 0.490). The multivariable Cox model did not show any difference in hazards for composite events between groups. CONCLUSIONS: In Chinese with young-onset non-type 1 diabetes, at least 2% of cases were contributed by monogenic diabetes, over 80% of which were accounted for by P/LP variants in common MODY genes. The incidence of diabetes complications was similar between patients with and without monogenic diabetes.

Young-Onset Diabetes in East Asians: From Epidemiology to Precision Medicine.

Precision diagnosis is the keystone of clinical medicine. In East Asians, classical type 1 diabetes is uncommon in patients with youngonset diabetes diagnosed before age of 40, in whom a family history, obesity, and beta-cell and kidney dysfunction are key features. Young-onset diabetes affects one in five Asian adults with diabetes in clinic settings; however, it is often misclassified, resulting in delayed or non-targeted treatment. Complex aetiologies, long disease duration, aggressive clinical course, and a lack of evidence-based guidelines have contributed to variable care standards and premature death in these young patients. The high burden of comorbidities, notably mental illness, highlights the numerous knowledge gaps related to this silent killer. The majority of adult patients with youngonset diabetes are managed as part of a heterogeneous population of patients with various ages of diagnosis. A multidisciplinary care team led by physicians with special interest in young-onset diabetes will help improve the precision of diagnosis and address their physical, mental, and behavioral health. To this end, payors, planners, and providers need to align and re-design the practice environment to gather data systematically during routine practice to elucidate the multicausality of young-onset diabetes, treat to multiple targets, and improve outcomes in these vulnerable individuals.

A novel electronic health record-based, machine-learning model to predict severe hypoglycemia leading to hospitalizations in older adults with diabetes: A territory-wide cohort and modeling study.

BACKGROUND: Older adults with diabetes are at high risk of severe hypoglycemia (SH). Many machine-learning (ML) models predict short-term hypoglycemia are not specific for older adults and show poor precision-recall. We aimed to develop a multidimensional, electronic health record (EHR)-based ML model to predict one-year risk of SH requiring hospitalization in older adults with diabetes. METHODS AND FINDINGS: We adopted a case-control design for a retrospective territory-wide cohort of 1,456,618 records from 364,863 unique older adults (age ≥65 years) with diabetes and at least 1 Hong Kong Hospital Authority attendance from 2013 to 2018. We used 258 predictors including demographics, admissions, diagnoses, medications, and routine laboratory tests in a one-year period to predict SH events requiring hospitalization in the following 12 months. The cohort was randomly split into training, testing, and internal validation sets in a 7:2:1 ratio. Six ML algorithms were evaluated including logistic-regression, random forest, gradient boost machine, deep neural network (DNN), XGBoost, and Rulefit. We tested our model in a temporal validation cohort in the Hong Kong Diabetes Register with predictors defined in 2018 and outcome events defined in 2019. Predictive performance was assessed using area under the receiver operating characteristic curve (AUROC), area under the precision-recall curve (AUPRC) statistics, and positive predictive value (PPV). We identified 11,128 SH events requiring hospitalization during the observation periods. The XGBoost model yielded the best performance (AUROC = 0.978 [95% CI 0.972 to 0.984]; AUPRC = 0.670 [95% CI 0.652 to 0.688]; PPV = 0.721 [95% CI 0.703 to 0.739]). This was superior to an 11-variable conventional logistic-regression model comprised of age, sex, history of SH, hypertension, blood glucose, kidney function measurements, and use of oral glucose-lowering drugs (GLDs) (AUROC = 0.906; AUPRC = 0.085; PPV = 0.468). Top impactful predictors included non-use of lipid-regulating drugs, in-patient admission, urgent emergency triage, insulin use, and history of SH. External validation in the HKDR cohort yielded AUROC of 0.856 [95% CI 0.838 to 0.873]. Main limitations of this study included limited transportability of the model and lack of geographically independent validation. CONCLUSIONS: Our novel-ML model demonstrated good discrimination and high precision in predicting one-year risk of SH requiring hospitalization. This may be integrated into EHR decision support systems for preemptive intervention in older adults at highest risk.

Comparison of ß-Cell Function and Insulin Sensitivity Between Normal-Weight and Obese Chinese With Young-Onset Type 2 Diabetes.

Normal-weight individuals with usual-onset type 2 diabetes have reduced ß-cell function and greater insulin sensitivity compared with their obese counterparts. The relative contribution of ß-cell dysfunction and insulin resistance to young-onset type 2 diabetes (YOD) among normal-weight individuals is not well established. In 44 individuals with YOD (24 with normal weight and 20 with obesity) and 24 healthy control individuals with normoglycemia (12 with normal weight and 12 with obesity), we conducted 2-h 12 mmol/L hyperglycemic clamps to measure acute (0-10 min) and steady-state (100-120 min) insulin and C-peptide responses, as well as insulin sensitivity index. Normal-weight individuals with YOD had lower acute insulin response, steady-state insulin and C-peptide responses, and a higher insulin sensitivity index compared with their obese counterparts with YOD. Compared with BMI-matched healthy control individuals, normal-weight individuals with YOD had lower acute and steady-state insulin and C-peptide responses but a similar insulin sensitivity index. The impairment of steady-state ß-cell response relative to healthy control individuals was more pronounced in normal-weight versus obese individuals with YOD. In conclusion, normal-weight Chinese with YOD exhibited worse ß-cell function but preserved insulin sensitivity relative to obese individuals with YOD and BMI-matched healthy individuals with normoglycemia. The selection of glucose-lowering therapy should account for pathophysiological differences underlying YOD between normal-weight and obese individuals.

Diabetes and infection: review of the epidemiology, mechanisms and principles of treatment.

An association between diabetes and infection has been recognised for many years, with infection being an important cause of death and morbidity in people with diabetes. The COVID-19 pandemic has re-kindled an interest in the complex relationship between diabetes and infection. Some infections occur almost exclusively in people with diabetes, often with high mortality rates without early diagnosis and treatment. However, more commonly, diabetes is a complicating factor in many infections. A reciprocal relationship occurs whereby certain infections and their treatments may also increase the risk of diabetes. People with diabetes have a 1.5- to 4-fold increased risk of infection. The risks are the most pronounced for kidney infection, osteomyelitis and foot infection, but are also increased for pneumonia, influenza, tuberculosis, skin infection and general sepsis. Outcomes from infection are worse in people with diabetes, with the most notable example being a twofold higher rate of death from COVID-19. Hyperglycaemia has deleterious effects on the immune response. Vascular insufficiency and neuropathy, together with altered skin, mucosal and gut microbial colonisation, contribute to the increased risk of infection. Vaccination is important in people with diabetes although the efficacy of certain immunisations may be compromised, particularly in the presence of hyperglycaemia. The principles of treatment largely follow those of the general population with certain notable exceptions.

Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry.

INTRODUCTION: Type 2 diabetes is preventable in subjects with impaired glucose tolerance based on 2-hour plasma glucose (2hPG) during 75 g oral glucose tolerance test (OGTT). We incorporated routine biochemistry to improve the performance of a non-invasive diabetes risk score to identify individuals with abnormal glucose tolerance (AGT) defined by 2hPG≥7.8 mmol/L during OGTT. RESEARCH DESIGN AND METHODS: We used baseline data of 1938 individuals from the community-based "Better Health for Better Hong Kong - Hong Kong Family Diabetes Study (BHBHK-HKFDS) Cohort" recruited in 1998-2003. We incorporated routine biochemistry in a validated non-invasive diabetes risk score, and evaluated its performance using area under receiver operating characteristics (AUROC) with internal and external validation. RESULTS: The AUROC of the original non-invasive risk score to predict AGT was 0.698 (95% CI, 0.662 to 0.733). Following additional inclusion of fasting plasma glucose, serum potassium, creatinine, and urea, the AUROC increased to 0.778 (95% CI, 0.744 to 0.809, p<0.001). Net reclassification improved by 31.9% (p<0.001) overall, by 30.8% among people with AGT and 1.1% among people without AGT. The extended model showed good calibration (χ2=11.315, p=0.1845) and performance on external validation using an independent data set (AUROC=0.722, 95% CI, 0.680 to 0.764). CONCLUSIONS: The extended risk score incorporating clinical and routine biochemistry can be integrated into an electronic health records system to select high-risk subjects for evaluation of AGT using OGTT for prevention of diabetes.

Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank.

AIMS/HYPOTHESIS: The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers. METHODS: From a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts. RESULTS: At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts. CONCLUSIONS/INTERPRETATION: Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.

1-year weight change after diabetes diagnosis and long-term incidence and sustainability of remission of type 2 diabetes in real-world settings in Hong Kong: An observational cohort study.

BACKGROUND: Clinical trials have demonstrated that remission of type 2 diabetes can be achieved following sustained weight loss. However, the feasibility of achieving diabetes remission through weight management in real-world settings remains unclear. In this study, we aimed to examine the association of weight change at 1 year after diabetes diagnosis with long-term incidence and sustainability of type 2 diabetes remission in real-world settings in Hong Kong. METHODS AND FINDINGS: This was a population-based observational cohort study. The territory-wide Risk Assessment and Management Programme for Diabetes Mellitus (RAMP-DM) provides regular comprehensive assessments of metabolic control and complication screening for people with diabetes in Hong Kong. We included 37,326 people with newly diagnosed type 2 diabetes who were enrolled in the RAMP-DM between 2000 and 2017, followed until 2019. Diabetes remission was defined as 2 consecutive HbA1c <6.5% measurements at least 6 months apart in the absence of glucose-lowering drugs (GLDs) and with no record of GLDs at least 3 months before these measurements. During a median follow-up of 7.9 years, 6.1% (2,279) of people achieved diabetes remission, with an incidence rate of 7.8 (95% CI: 7.5, 8.1) per 1,000 person-years. After adjusting for age at diabetes diagnosis, sex, assessment year, body mass index, other metabolic indices, smoking, alcohol drinking, and medication use, the hazard ratio (HR) for diabetes remission was 3.28 (95% CI: 2.75, 3.92; p < 0.001) for people with ≥10% weight loss within 1 year of diagnosis, 2.29 (95% CI: 2.03, 2.59; p < 0.001) for those with 5% to 9.9% weight loss, and 1.34 (95% CI: 1.22, 1.47; p < 0.001) for those with 0% to 4.9% weight loss compared to people with weight gain. During a median follow-up of 3.1 years, 67.2% (1,531) of people who had achieved diabetes remission returned to hyperglycaemia, with an incidence rate of 184.8 (95% CI: 175.5, 194.0) per 1,000 person-years. The adjusted HR for returning to hyperglycaemia was 0.52 (95% CI: 0.41, 0.65; p < 0.001) for people with ≥10% weight loss, 0.78 (95% CI: 0.68, 0.92; p = 0.002) for those with 5% to 9.9% weight loss, and 0.90 (95% CI: 0.80, 1.01; p = 0.073) for those with 0% to 4.9% weight loss compared to people with weight gain. Diabetes remission was associated with a 31% (HR: 0.69, 95% CI: 0.52, 0.93; p = 0.014) decreased risk of all-cause mortality. The main limitation of the study is that the reliability of HbA1c used to define diabetes remission can be affected by other medical conditions. Furthermore, we did not have data on bariatric surgery. CONCLUSIONS: In this study, greater weight loss within the first year of diabetes diagnosis was associated with an increased likelihood of achieving diabetes remission and a decreased risk of returning to hyperglycaemia among those who had achieved diabetes remission. However, both the incidence of diabetes remission and the probability of its long-term sustainability were low with conventional management in real-world settings, in an era when the importance of weight loss was not fully appreciated. Our study provides evidence for policymakers to design and implement early weight management interventions and diabetes remission initiatives.

Early treatment with dipeptidyl-peptidase 4 inhibitors reduces glycaemic variability and delays insulin initiation in type 2 diabetes: A propensity score-matched cohort study.

AIMS: To examine whether early treatment intensification using dipeptidyl-peptidase 4 inhibitors (DPP4i) delays insulin initiation in Chinese patients diagnosed with type 2 diabetes for less than 5 years. MATERIALS AND METHODS: In a territory-wide prospective cohort study, patients with type 2 diabetes initiating DPP4i at diabetes duration <2 years (early intensification) and 3-5 years (late intensification) were matched using 1:1 propensity-score matching (n = 908 in each arm). We used Cox regression to compare the risk of insulin initiation between the two groups. We explored the interactive and mediation effects of glycated haemoglobin (HbA1c) variability score (HVS), defined as the percentage of HbA1c varying by ≥0.5% compared with preceding values. RESULTS: Of 1816 patients (60.7% men, mean age 54.4 ± 11.9 years), 92.4% and 71.9% were treated with metformin and sulphonylureas respectively at DPP4i initiation. Early DPP4i intensification [hazard ratio (HR) 0.71, (95% CI 0.58-0.68)] and low HVS (<50%) (HR = 0.40, 0.33-0.50) were associated with delayed insulin initiation during a median 4.08 years of follow-up. Early intensification with low HVS had the lowest risk versus late intensification with high HVS (HR = 0.30, 0.22-0.40) (pinteraction  = 0.013). HVS mediated 19.5% of the total effect of early DPP4i intensification on delaying insulin initiation. The late and early intensification groups had similar HbA1c at month 0 (8.4 ± 1.3% vs. 8.4 ± 1.5%) and month 3 (7.6 ± 1.2% vs. 7.6 ± 1.3%) after DPP4i initiation. By month 12, HbA1c in the late intensification group deteriorated (7.9 ± 1.4%) but remained stable in the early intensification group (7.6 ± 1.4%, p = 0.001) with persistent between-group difference over 72 months (8.2 ± 1.7% vs. 7.7 ± 1.6%, p = 0.001). CONCLUSIONS: In type 2 diabetes, early DPP4i intensification delayed insulin initiation, partially explained by reduced glycaemic variability.

Impact of Body Composition and Anemia on Accuracy of a Real-Time Continuous Glucose Monitor in Diabetes Patients on Continuous Ambulatory Peritoneal Dialysis.

Continuous glucose monitoring (CGM) is proposed as an alternative for glycemic assessment in peritoneal dialysis, but volume overload and anemia may affect sensor accuracy. This is an exploratory analysis of a study of Guardian Connect™ with Guardian Sensor™ 3 in 30 participants with diabetes on continuous ambulatory peritoneal dialysis (CAPD) (age [mean ± standard deviation] 64.7 ± 5.6 years, 23 men, body mass index [BMI] 25.4 ± 3.9 kg/m2, blood hemoglobin [Hb] 10.7 ± 1.3 g/dL). The mean absolute relative difference (MARD) was calculated between paired sensor and YSI 2300 STAT venous glucose readings (n = 941) during an 8-h in-clinic session with glucose challenge. Body composition was evaluated using bioimpedance. The overall MARD was 10.4% (95% confidence interval 9.6-11.7). There were no correlations between BMI, extracellular water, relative hydration index, and lean or fat mass with MARD. No correlations were observed between MARD and Hb (r = 0.016, P > 0.05). In summary, this real-time CGM demonstrated good accuracy in CAPD with minimal influence from body composition and anemia.

Temporal associations of diabetes-related complications with health-related quality of life decrements in Chinese patients with type 2 diabetes: A prospective study among 19 322 adults-Joint Asia Diabetes Evaluation (JADE) register (2007-2018).

BACKGROUND: Patients with type 2 diabetes (T2D) are at high risk of developing multiple complications, affecting their health-related quality of life (HRQoL). Existing studies only considered impact of complication on HRQoL in the year of occurrence but not its residual impacts in subsequent years. We investigated temporal impacts of diabetes-related complications on HRQoL in a 12-year prospective cohort of ambulatory Chinese patients with T2D enrolled in the clinic-based Joint Asia Diabetes Evaluation (JADE) Register. METHODS: HRQoL utility measures were derived from EuroQol five-dimensional three-level questionnaire (EQ-5D-3L) questionnaires completed by 19 322 patients with T2D in Hong Kong (2007-2018). Temporal EQ-5D utility decrements associated with subtypes of cardiovascular-renal events were estimated using generalized linear regression model after stepwise selection of covariates with p < .01 as cutoff. RESULTS: In this cohort (mean ± SD age:61.2 ± 11.5 years, 55.3% men, median [interquartile range] duration of diabetes:10.1 [3.0-15.0] years, glycated hemoglobin [HbA1C ] 7.5 ± 1.5%), EQ-5D utility was 0.860 ± 0.163. The largest HRQoL decrements were observed in year of occurrence of hemorrhagic stroke (-0.230), followed by ischemic stroke (-0.165), peripheral vascular disease (-0.117), lower extremity amputation (-0.093), chronic kidney disease (CKD) G5 without renal replacement therapy (RRT) (-0.079), congestive heart failure (CHF) (-0.061), and CKD G3-G4 without RRT (-0.042). Residual impacts on HRQoL persisted for 2 years after occurrence of CHF or ischemic stroke and 1 year after hemorrhagic stroke or CKD G3-G4 without RRT. CONCLUSION: This is the first comprehensive report on temporal associations of HRQoL decrements with subtypes of diabetes-related complications in ambulatory Asian patients with T2D. These data will improve the accuracy of cost-effectiveness analysis of diabetes interventions at an individual level in an Asian setting.

Comparison of beta-cell function between Hong Kong Chinese with young-onset type 2 diabetes and late-onset type 2 diabetes.

AIMS: We compared beta-cell function in Chinese with type 2 diabetes diagnosed at age < 40 years (young-onset diabetes, YOD) and ≥ 40 years (late-onset diabetes, LOD). METHODS: In this cross-sectional study, we selected participants from two cohorts of people with type 2 diabetes recruited in 1996-2012 (n = 4,376) and 2020-2021 (n = 794). Multivariable linear regression models were applied to compare homeostasis model assessment of beta-cell function (HOMA2-%B) and fasting plasma C-peptide across diabetes duration at enrolment between YOD and LOD. RESULTS: The YOD group (n = 1,876, mean [SD] age: 39.9 [7.5] years, median [IQR] diabetes duration: 6 [2-12] years) was more likely to have family history of diabetes (61.6 % vs 43.6 %), obesity (41.9 % vs 26.8 %), dyslipidaemia (61.7 % vs 54.4 %), and worse glycaemic control (mean HbA1c 7.7 % vs 7.4 %) than those with LOD (n = 3,294, age: 60.8 [10.6] years, diabetes duration: 5 [1-10] years). When compared to people with LOD, HOMA2-%B and fasting plasma C-peptide were lower in the YOD group, consistently among those with BMI < 27.5 kg/m2 and HOMA2-IR ≤ 1.6 (median value), adjusted for year at enrolment, sex, diabetes duration, family history of diabetes, HbA1c, weight and lipid indices (p < 0.01). Cross-sectionally, the slopes of decline in HOMA2-%B by diabetes duration were greater in YOD than LOD among individuals with BMI < 27.5 kg/m2 (p-interaction = 0.015). CONCLUSIONS: Chinese with YOD had accelerated loss of beta-cell function than those with LOD especially in non-obese individuals.

Age- and sex-specific hospital bed-day rates in people with and without type 2 diabetes: A territory-wide population-based cohort study of 1.5 million people in Hong Kong.

BACKGROUND: Type 2 diabetes affects multiple systems. We aimed to compare age- and sex-specific rates of all-cause and cause-specific hospital bed-days between people with and without type 2 diabetes. METHODS AND FINDINGS: Data were provided by the Hong Kong Hospital Authority. We included 1,516,508 one-to-one matched people with incident type 2 diabetes (n = 758,254) and those without diabetes during the entire follow-up period (n = 758,254) between 2002 and 2018, followed until 2019. People with type 2 diabetes and controls were matched for age at index date (±2 years), sex, and index year (±2 years). We defined hospital bed-day rate as total inpatient bed-days divided by follow-up time. We constructed negative binominal regression models to estimate hospital bed-day rate ratios (RRs) by age at diabetes diagnosis and sex. All RRs were stratified by sex and adjusted for age and index year. During a median of 7.8 years of follow-up, 60.5% (n = 459,440) of people with type 2 diabetes and 56.5% (n = 428,296) of controls had a hospital admission for any cause, with a hospital bed-day rate of 3,359 bed-days and 2,350 bed-days per 1,000 person-years, respectively. All-cause hospital bed-day rate increased with increasing age in controls, but showed a J-shaped relationship with age in people with type 2 diabetes, with 38.4% of bed-days in those diagnosed <40 years caused by mental health disorders. Type 2 diabetes was associated with increased risks for a wide range of medical conditions, with an RR of 1.75 (95% CI [confidence interval] [1.73, 1.76]; p < 0.001) for all-cause hospital bed-days in men and 1.87 (95% CI [1.85, 1.89]; p < 0.001) in women. The RRs were greater in people with diabetes diagnosed at a younger than older age and varied by sex according to medical conditions. Sex differences were most notable for a higher RR for urinary tract infection and peptic ulcer, and a lower RR for chronic kidney disease and pancreatic disease in women than men. The main limitation of the study was that young people without diabetes in the database were unlikely to be representative of those in the Hong Kong general population with potential selection bias due to inclusion of individuals in need of medical care. CONCLUSIONS: In this study, we observed that type 2 diabetes was associated with increased risks of hospital bed-days for a wide range of medical conditions, with an excess burden of mental health disorders in people diagnosed at a young age. Age and sex differences should be considered in planning preventive and therapeutic strategies for type 2 diabetes. Effective control of risk factors with a focus on mental health disorders are urgently needed in young people with type 2 diabetes. Healthcare systems and policymakers should consider allocating adequate resources and developing strategies to meet the mental health needs of young people with type 2 diabetes, including integrating mental health services into diabetes care.

Incident cardiovascular-kidney disease, diabetic ketoacidosis, hypoglycaemia and mortality in adult-onset type 1 diabetes: a population-based retrospective cohort study in Hong Kong.

Background: Type 1 diabetes can occur at any age. The majority of literature on type 1 diabetes were reported in children whereas adult-onset type 1 diabetes is less well characterised. This study aims to compare the risk of diabetes-related complications and mortality in Chinese with adult-onset type 1 diabetes versus those with youth-onset type 1 diabetes and adult-onset type 2 diabetes. Methods: Between 2000 and 2018, 2738 people with type 1 and 499,288 with type 2 diabetes underwent metabolic and complication assessment in Hong Kong Hospital Authority. They were followed for incident diabetic ketoacidosis (DKA), severe hypoglycaemia, end-stage kidney disease (ESKD), cardiovascular disease (CVD) and all-cause mortality until 2019. Findings: In multivariable Cox regression adjusted for sex, diabetes duration and calendar year, people with type 1 diabetes diagnosed aged ≥40 years had a lower hazard of DKA (hazard ratio HR [95% CI] 0.47 [0.32-0.70]) but higher hazards of severe hypoglycaemia (HR 1.37 [1.13-1.67]), ESKD (HR 4.62 [2.90-7.37]), CVD (HR 11.44 [6.92-18.91]) and mortality (HR 16.22 [11.43-23.02]) versus those diagnosed aged <20 years. Compared with peers with type 2 diabetes presenting at comparable age, people with type 1 diabetes diagnosed aged ≥40 years had higher age-, sex- and diabetes duration-adjusted hazards of DKA (HR 19.87 [13.95-28.31]), severe hypoglycaemia (HR 3.26 [2.81-3.80]), ESKD (HR 1.58 [1.20-2.09]) and mortality (HR 2.26 [1.96-2.60]), and a similar hazard of CVD (HR 1.11 [0.87-1.43]). These associations remained constant after adjustment for metabolic indices. Interpretation: People with type 1 diabetes diagnosed in late adulthood had elevated risks of a broad range of complications and mortality compared with people with youth-onset type 1 diabetes and people with type 2 diabetes presenting at same age bands. Funding: This study did not receive any specific funding.

Identification of a Common Variant for Coronary Heart Disease at PDE1A Contributes to Individualized Treatment Goals and Risk Stratification of Cardiovascular Complications in Chinese Patients With Type 2 Diabetes.

OBJECTIVE: In this study we aim to unravel genetic determinants of coronary heart disease (CHD) in type 2 diabetes (T2D) and explore their applications. RESEARCH DESIGN AND METHODS: We performed a two-stage genome-wide association study for CHD in Chinese patients with T2D (3,596 case and 8,898 control subjects), followed by replications in European patients with T2D (764 case and 4,276 control subjects) and general populations (n = 51,442-547,261). Each identified variant was examined for its association with a wide range of phenotypes and its interactions with glycemic, blood pressure (BP), and lipid controls in incident cardiovascular diseases. RESULTS: We identified a novel variant (rs10171703) for CHD (odds ratio 1.21 [95% CI 1.13-1.30]; P = 2.4 × 10-8) and BP (ß ± SE 0.130 ± 0.017; P = 4.1 × 10-14) at PDE1A in Chinese T2D patients but found only a modest association with CHD in general populations. This variant modulated the effects of BP goal attainment (130/80 mmHg) on CHD (Pinteraction = 0.0155) and myocardial infarction (MI) (Pinteraction = 5.1 × 10-4). Patients with CC genotype of rs10171703 had >40% reduction in either cardiovascular events in response to BP control (2.9 × 10-8 < P < 3.6 × 10-5), those with CT genotype had no difference (0.0726 < P < 0.2614), and those with TT genotype had a threefold increase in MI risk (P = 6.7 × 10-3). CONCLUSIONS: We discovered a novel CHD- and BP-related variant at PDE1A that interacted with BP goal attainment with divergent effects on CHD risk in Chinese patients with T2D. Incorporating this information may facilitate individualized treatment strategies for precision care in diabetes, only when our findings are validated.

Higher incidence of cardiovascular-kidney complications in Chinese with youth-onset type 2 diabetes versus youth-onset type 1 diabetes attenuated by control of cardio-metabolic risk factors: A population-based prospective cohort study in Hong Kong.

AIMS: To determine and compare the incidence of diabetes complications in Chinese with youth-onset type 2 and type 1 diabetes. METHODS: We conducted a population-based prospective cohort study, including 1,260 people with type 2 diabetes and 1,227 with type 1 diabetes diagnosed at age < 20 years who underwent metabolic and complication assessment in Hong Kong Hospital Authority between 2000 and 2018. They were followed for incident cardiovascular disease (CVD), end-stage kidney disease (ESKD) and all-cause death until 2019. Multivariable Cox regression analysis was applied to compare the risks of these complications in type 2 versus type 1 diabetes. RESULTS: People with type 1 diabetes (median age: 20 years, median diabetes duration: 9 years) and type 2 diabetes (median age: 21 years, median diabetes duration: 6 years) were followed for a mean period of 9.2 and 8.8 years respectively. The risks of CVD (HR [95 % CI] 1.66 [1.01-2.72]) and ESKD (HR 1.96 [1.27-3.04]) but not death (HR 1.10 [0.72-1.67]) were higher in type 2 versus type 1 diabetes, adjusted for age at diagnosis, diabetes duration and sex. The association became nonsignificant with further adjustment for glycaemic and metabolic control. Youth-onset type 2 diabetes conferred mortality excess (standardized mortality ratio 4.15 [3.28-5.17]) to age- and sex-matched general population. CONCLUSIONS: People with youth-onset type 2 diabetes had higher incidence rates of CVD and ESKD than type 1 diabetes. The excess risks in type 2 diabetes were removed after adjusted for cardio-metabolic risk factors.